Könyv IoT and AI in Agriculture Tofael Ahamed

IoT and AI in Agriculture

Smart Automation Systems for increasing Agricultural Productivity to Achieve SDGs and Society 5.0

Szerző: Tofael Ahamed
Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
78 458 Ft
This book covers smart agricultural space and its further development with an emphasis on ultra-savi...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2024
oldal
520
EAN
9789819712625
Enbook ID
44751188
Súly
883
Méretek
155 x 235

Teljes leírás

This book covers smart agricultural space and its further development with an emphasis on ultra-saving labor shortages using AI-based technologies. A transboundary approach, as well as artificial intelligence (AI) and big data for bioinformatics, are required to increase timeliness and supplement the labor shortages, ensure the safety of intangible labor migration system to achieve one of the sustainable development goals (SDG) to secure food security (Society 5.0, SDG 1 and 2). With this in mind, the book focuses on the solution through smart Internet of Things (IoT) and AI-based agriculture, such as automation navigation, insect infestation, and decreasing agricultural inputs such as water and fertilizer, to maintain food security while ensuring environmental sustainability. Readers will gain a solid foundation for developing new knowledge through the in-depth research and education orientation of the book on how the deployment of outdoor and indoor sensors, AI/machine learning (ML), and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms is nurturing and driving the pace of smart agriculture outdoor and indoors at this current time. Furthermore, the book introduces the smart system for automation challenges that are important for an unmanned system for considering safety and security points. The book is designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science. The greatest care has been made to deliver a diverse range of resource areas, as well as enormous insights into the significance and scope of IoT, AI, and ML in the development of intelligent digital farming and smart agriculture, providing comprehensive information to the intended readers.

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